• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.501-509
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• 2006

The safety of levee that depends on the river flood elevation has been regarded as very important keys to build up various flood prevention systems. However, deterministic methods for computation of water surface profile cannot reflect the effect of possible inaccuracies in the input parameters. The purpose of this study is to develop a methodology of uncertainty computation of design flood level based on steady flow analysis and Monte Carlo simulation. This study addresses the uncertainty of water surface elevation by Manning's coefficients, design discharges, river cross sections and boundary condition. Monte Carlo simulation with the variations of these parameters is performed to quantify the variations of water surface elevations in a river. The proposed model has been applied to the Kumho-river. The reliability analysis was performed within 38.5 km (95 sections) reach considered the variations of the above-mentioned parameters. Overtopping risks were evaluated by comparing the elevations of the flood condition with the those of the levees. The results show that there is a necessity which will raise the levee elevation between 1 cm and 56 cm at 7 sections. The model can be used for preparing flood risk maps, flood forecasting systems and establishing flood disaster mitigation plans as well as complement of conventional levee design.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.39-45
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• 2024

Container volume is a very important factor in accurate evaluation of port performance, and accurate prediction of effective port development and operation strategies is essential. However, it is difficult to improve the accuracy of container volume prediction due to rapid changes in the marine industry. To solve this problem, it is necessary to analyze the impact on port performance using the Internet of Things (IoT) and apply it to improve the competitiveness and efficiency of Busan Port. Therefore, this study aims to develop a prediction model for predicting the future container volume of Busan Port, and through this, focuses on improving port productivity and making improved decision-making by port management agencies. In order to predict port container volume, this study introduced the Extreme Gradient Boosting (XGBoost) technique of a machine learning model. XGBoost stands out of its higher accuracy, faster learning and prediction than other algorithms, preventing overfitting, along with providing Feature Importance. Especially, XGBoost can be used directly for regression predictive modelling, which helps improve the accuracy of the volume prediction model presented in previous studies. Through this, this study can accurately and reliably predict container volume by the proposed method with a 4.3% MAPE (Mean absolute percentage error) value, highlighting its high forecasting accuracy. It is believed that the accuracy of Busan container volume can be increased through the methodology presented in this study.

• Journal of the Korean Society of Radiology
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• v.83 no.2
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• pp.265-283
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• 2022

To develop Korean coronavirus disease (COVID-19) chest imaging justification guidelines, eight key questions were selected and the following recommendations were made with the evidence-based clinical imaging guideline adaptation methodology. It is appropriate not to use chest imaging tests (chest radiograph or CT) for the diagnosis of COVID-19 in asymptomatic patients. If reverse transcription-polymerase chain reaction testing is not available or if results are delayed or are initially negative in the presence of symptoms suggestive of COVID-19, chest imaging tests may be considered. In addition to clinical evaluations and laboratory tests, chest imaging may be contemplated to determine hospital admission for asymptomatic or mildly symptomatic un-hospitalized patients with confirmed COVID-19. In hospitalized patients with confirmed COVID-19, chest imaging may be advised to determine or modify treatment alternatives. CT angiography may be considered if hemoptysis or pulmonary embolism is clinically suspected in a patient with confirmed COVID-19. For COVID-19 patients with improved symptoms, chest imaging is not recommended to make decisions regarding hospital discharge. For patients with functional impairment after recovery from COVID-19, chest imaging may be considered to distinguish a potentially treatable disease.

• Smart Media Journal
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• v.13 no.4
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• pp.33-48
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• 2024

With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.10 no.1
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• pp.63-75
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• 2012

This paper gives some basic requirements and preferences of various geological environmental conditions for the final deep geological repository of spent nuclear fuel (SNF). This study also indicates how the requirements and preferences are to be considered prior to the selection of sites for a site investigation as well as the final disposal in Korea. The results of the study are based on the knowledge and experience from the IAEA and NEA/OECD as well as the advanced countries in SNF disposal project. This study discusses and suggests preliminary guideline of the disposal requirements including geological, mechanical, thermal, hydrogeological, chemical and transport properties of host rock with long term geological stabilities which influence the functions of a multi-barrier disposal system. To apply and determine whether requirements and preferences for a given parameter are satisfied at different stages during a site selection and suitability assessment of a final disposal site, the quantitative criteria in each area should be formulated with credibility through relevant research and development efforts for the deep geological environment during the site screening and selection processes as well as specific studies such as productions of safety cases and validation studies using a generic underground research laboratory (URL) in Korea.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.12
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• pp.803-812
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• 2014

This study assesses the strategy and performance of Eco-industrial Park (EIP) initiative implemented by Korea Industrial Complex Corporation (KICOX) with the support of Ministry of Trade, Industry and Energy (MOTIE), Korea since 2005 to 2013 and recommends future directions. After the concept of EIP based on industrial symbiosis (IS) is introduced, the background and implementation procedure of the EIP initiative are described. Then, economic and environmental achievement was assessed. During the project periods (2005-2013), 449 industrial symbiosis project were explored, among which 296 projects have been implemented. Among (Of these 296 projects,) them, 244 projects have been completed in which 118 projects have been commercialized which shows 48% commercialization rate of the completed projects. Through these commercialized projects, around 311.1 billion won/year of economic benefits and reduction of waste by-products of 828,113 tons/year, wastewater of 215,517 tons/year, reduction in energy consumption of 250,475 toe/year and GHG emission reduction of 1,107,189 $tCO_2/year$ were achieved. This results confirmed that EIP initiative based on industrial symbiosis can enhance eco-efficiency of industrial parks and harmonize economy and environment. However, there are obstacles like absence of interagency coordination and cooperation, laws and institutional barriers, increased demand for local governments, funding for project investment. Thus, to utilize EIP initiative as a strategic tool for competiveness and environmental management of industrial parks, it needs intergovernmental collaboration and interdisciplinary approach to lower barrier in implementation.

• Korean Chemical Engineering Research
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• v.52 no.4
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• pp.467-474
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• 2014

Preliminary design in chemical process furnishes economic feasibility through calculation of both mass balance and energy balance and makes it possible to produce a desired product under the given conditions. Through this design stage, the process possesses unchangeable characteristics, since the materials, reactions, unit configuration, and operating conditions were determined. Unique characteristics could be very economic, but it also implies various potential risk factors as well. Therefore, it becomes extremely important to design process considering both economics and safety by integrating process simulation and quantitative risk analysis during preliminary design stage. The target of this study is LNG liquefaction process. By the simulation using Aspen HYSYS and quantitative risk analysis, the design variables of the process were determined in the way to minimize the inherent explosion risks and operating cost. Instead of the optimization tool of Aspen HYSYS, the optimization was performed by using stochastic optimization algorithm (Covariance Matrix Adaptation-Evolution Strategy, CMA-ES) which was implemented through automation between Aspen HYSYS and Matlab. The research obtained that the important variable to enhance inherent safety was the operation pressure of mixed refrigerant. The inherent risk was able to be reduced about 4~18% by increasing the operating cost about 0.5~10%. As the operating cost increases, the absolute value of risk was decreased as expected, but cost-effectiveness of risk reduction had decreased. Integration of process simulation and quantitative risk analysis made it possible to design inherently safe process, and it is expected to be useful in designing the less risky process since risk factors in the process can be numerically monitored during preliminary process design stage.

• Journal of Environmental Policy
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• v.8 no.2
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• pp.83-118
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• 2009

Clean Development Mechanism(CDM) projects under the Kyoto Protocol have two objectives. One is to assist the Parties included in Annex I in achieving compliance with their quantified emission limitation and reduction commitments in cost-effective ways by allowing them to implement emission reduction projects in Non-Annex I countries and receive CERs, which will offset their reduction commitments. The other is to assist Parties not included in Annex I in achieving sustainable development and technology transfers through investments by Annex I countries. However, in reality, it is said that the former objective is achievable but the latter is not. In this light, this article suggests sustainability appraisal criteria applicable for Korea. Among various methodologies, we used the 'multi-attributes utility theory(MAUT)'; one of the 'multi-criteria analysis (MCA)' methodologies judged to be the most practical and relevant. Based on the guidelines of the MAUT methodology, we identified sustainability criteria that meet the guidelines. We took two tracks, the first to find the preferences of Korean experts, and the other to check foreign cases. In all, 37 preliminary criteria were suggested to Korean experts and each criterion was scored, from between 1 and 3, in terms of relevance, possibility of real improvement, easiness of data collection, and preferences. We combined foreign cases and the results of a survey conducted in Korea and selected 12 core criteria and 10 additional criteria. After that, all the criteria were converted into indicators. The indicators were applied to a CDM project for case study. We chose the "Sihwa Tidal Power Project", which is currently the biggest tidal power plant in the world. Twelve core indicators and 3 additional indicators were applied. In order to weight each indicator, the 'analytical hierarchy process (AHP)' was used. A total of 30 experts were asked to suggest weights and 21 answered. Among them, only 14 respondents were proven to meet the consistency ratio. We analyzed the 14 responses through Expert Choice and the CDM project was scored (+)53.082. In addition, sensitivity analysis was undertaken with the result of (+)44.667 to (+)65.522. As a result of this study, it was proven that this project would contribute to the sustainable development of Korea.

• Clinical and Experimental Pediatrics
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• v.46 no.1
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• pp.11-16
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• 2003

Purpose : Iron deficiency is still the most common nutrient deficient disorder despite the improvement in general health and nutrition. This study is designed to evaluate the dietary history of infants and young children with iron deficiency anemia(IDA) and the effects of nutritional counseling. Methods : This study was conducted on 120 children from 6 to 36 months of age with IDA. Their parents completed a questionnaire and took counsel for nutrition. IDA was defined as Hb <11.0 g/dL, ferritin <10 ng.mL or transferrin saturation <15%, or Hb increase >1 g/dL after iron preparation. The questionnaire consisted of their feeding patterns, weaning time and kinds of food. Results : In the 120 infants and young children aged from 6 to 36 months, the parents of 82 cases was counseled about nutrition. Fifty six infants among 82 cases have started weaning and the main foods of weaning were rice and/or rice gruel. Nutritional problems in weaning were that some children over one year of age were using a bottle, and parents restricted weaning food at will because of allergic disease or chronic disease. Most parents were satisfied with the nutritional counseling given from a clinical dietitian and showed good compliance. Conclusion : Many infants and young children with IDA were provided with non iron-fortified foods and made an inadequate wean. Most parents were satisfied with the nutritional counseling and showed good compliance. The need of dietary counseling was required for prevention and treatment of iron deficiency anemia because of inadequate weaning.